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Graduate Exam Abstract


minda Le

Ph.D. Final
March 11, 2013, 2pm
N/A
MICROPHYSICAL RETRIEVAL AND PROFILE CLASSIFICATION FOR GPM DUAL-FREQUENCY PRECIPITATION RADAR AND THE GROUND VALIDATION

Abstract: The Global Precipitation Measurement (GPM) mission
is planned to be the next satellite mission
following Tropical Rainfall Measurement Mission
(TRMM) jointly by National Aeronautic and Space
Administration (NASA) of USA and the Japanese
Aerospace Exploration Agency (JAXA) with
additional partners namely the Centre National
d’Études Spatiales (CNES), the Indian Space
Research Organization (ISRO), the National Oceanic
and Atmospheric Administration (NOAA), the
European Organization for the Exploitation of
Meteorological Satellites (EUMETSAT), and others.
The core satellite of GPM mission will be equipped
with a dual frequency precipitation radar (DPR)
operating at Ku- (13.6 GHz) and Ka- (35.5 GHz)
band with the capability to cover 65 latitude of
the earth. One primary goal of the DPR is to
improve accuracy in estimation of drop size
distribution (DSD) parameters of precipitation
particles. The estimation of the DSD parameters
helps to achieve more accurate estimation of
precipitation rate. The DSD is also centrally
important in the determination of the
electromagnetic scattering properties of
precipitation media. The combination of data from
the two frequency channels, in principle, can
provide more accurate estimates of DSD parameters
than the TRMM Precipitation radar (TRMM PR) with
Ku- band channel only. In this research, a
methodology is developed to retrieve DSD
parameters for GPM-DPR.

Profile classification is a critical module in the
microphysical retrieval system for GPM-DPR. The
nature of microphysical models and equations to
use in the DSD retrieval algorithm are determined
by the precipitation type of each profile and the
phase state of hydrometeors. In the GPM era, Ka-
band channel enables the detection of light rain
or snowfall in the mid- and high- latitudes
compared to the TRMM PR (Ku- band only). GPM-DPR
offers dual-frequency observations (measured
reflectivity at Ku- band:Z_m (K_u ) and measured
reflectivity at Ka- band: Z_m (K_a )) along each
vertical profile, which provide additional
information for investigating the microphysical
properties using the difference in measured radar
reflectivities at the two frequencies, a quantity
often called the measured dual-frequency ratio
(DFRm) can be defined (DFRm=Z_m (K_u )-Z_m (K_a )
). Both non-Rayleigh scattering effects and
attenuation difference control the shape of the
DFRm profile. Its pattern is determined by the
forward and backscattering properties of the mixed
phase and rain and the backscattering properties
of the ice. Therefore, DFRm could provide better
performance in precipitation type classification
and hydrometeor profile characterization than TRMM
PR. In this research, two methods namely
precipitation type classification method (PCM) and
hydrometeor profile characterization (HPC) method
are developed to perform profile classification
for GPM-DPR using DFRm profile and its range
variability. The methods have been implemented
into GPM-DPR day one algorithm.

Ground validation is an integral part of all
satellite precipitation missions. Similar to TRMM,
the GPM validation falls in the general class of
validation and integration of information from
space-borne observing platforms with a variety of
ground-based measurements. Dual polarization
ground radar is a powerful tool that can be used
to address a number of important questions that
arise in the validation process, especially those
associated with precipitation microphysics and
algorithm development. Extensive research has also
been done regarding accurate retrievals of rain
DSDs as well as attenuation correction for dual-
polarization ground radar operating at S-, C- and
X- band by using polarimetric measurements.
However, polarimetric ground radar operating at a
single frequency channel has limitation on DSD
retrieval beyond rain region. A dual frequency and
dual polarization Doppler radar (D3R) operating at
the same frequency channels as GPM-DPR has been
built. In this research, an algorithm is
developed to retrieve DSD parameter for this D3R
radar which will serve as GPM-DPR ground
validation instrument.


Adviser: Dr. V. Chandrasekar
Co-Adviser: N/A
Non-ECE Member: Dr. Mielke, Statistics
Member 3: Dr. Jayasumana, ECE
Addional Members: Dr. Notaros, ECE

Publications:
Journal papers:

[1] M. Le and V. Chandrasekar, Raindrop Size Distribution Retrieval from Dual Frequency and Dual Polarization Radar, IEEE Transactions on Geoscience and Remote Sensing, Volume 50, No 5, May, 2012, pp 1748-1758.

[2] M. Le and V. Chandrasekar, Precipitation Type Classification Method for Dual Frequency Precipitation Radar (DPR) on board the GPM, IEEE Transactions on Geoscience and Remote Sensing, Volume 51, issue 3, 2012.

[3] M. Le and V. Chandrasekar, Hydrometeor profile characterization method for dual frequency precipitation radar (DPR) on board the GPM. IEEE Transactions on Geoscience and Remote Sensing, Volume 51, issue 6, 2012.

[4] A. Alqudoh, V. Chandrasekar and Minda Le, Investigating rainfall estimation from radar measurements using neural network. Accepted by Journal of Natural Hazards and Earth System Sciences (NHESS), 2012.

Conference papers:

[1] M. Le and V. Chandrasekar, Evaluation of GPM candidate algorithms on hurricane observations, AGU (American Geophysical Union) fall meeting, 2012, San Francisco, CA.

[2] M. Le and V. Chandrasekar, A potential DSD retrieval process for dual-frequency precipitation radar (DPR) on board GPM, SPIE Asia-pacific remote sensing 2012, Kyoto, Japan.

[3] V. Chandrasekar, Direk, Khajonrat and Minda, Le, Global vertical reflectivity profile analysis using TRMM PR observations: Application to tropical storms, The 4th Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) Mission International Science Conference, 2012, Tokyo, Japan.

[4] M. Le and V. Chandrasekar, Recent updates on precipitation classification and hydrometeor identification algorithm for GPM-DPR, Geoscience science and remote sensing symposium, IGARSS’2012, IEEE International, Munich, Germany.

[5] V. Chandrasekar, Mathew Schwaller, Manuel Vega, James Carswell, Kumar Vijay Mishra, Alex Steinberg, Cuong Nguyen, Minda Le, Joseph Hardin, Francesc Junyent, Jim George, Dual-frequency dual-polarized doppler radar (D3R) system for GPM ground validation: update and recent field observations, IGARSS’2012, IEEE International, Munich, Germany.

[6] V. Chandrasekar, Minda Le, Amin Alqudah and Delbert Willie, Global map of precipitation: An example of data fusion from satellite, ground radar and rain gauge. 92nd American Meteorological Society Annual Meeting , January 22-26, 2012.

[7] M. Le and V. Chandrasekar, Precipitation Type and Profile Classification for GPM-DPR, Geoscience science and remote sensing symposium, IGARSS’2011, IEEE International, Vancouver, Canada.

[8] M. Le and V. Chandrasekar, GPM Dual-frequency Ratio Characteristics in the Melting Layer, 35st Conference on Radar Meteorology, 26-30 September 2011, American Meteorology Society, Pittsburgh, PA.

[9] M. Le ,V. Chandrasekar and S. Lim, Microphysical retrieval from dual-frequency precipitation radar board GPM, Geoscience science and remote sensing symposium, IGARSS’2010, IEEE International, Honolulu, USA.

[10] M. Le ,V. Chandrasekar and S. Lim, Microphysical retrieval of dual-polarization and dual-frequency ground radar from GPM ground validation, Geoscience science and remote sensing symposium, IGARSS’ 2010, IEEE International, Honolulu, USA.

[11] M. Le and V. Chandrasekar , Dual frequency and dual polarization radar observations of precipitation and retrievals for GPM ground validation. Proc USNC-URSI ’2010, Boulder, Colorado.

[12] M. Le, V. Chandrasekar and S.Lim, Combined Ku and Ka band observations of precipitation and retrievals for GPM ground validation, Geoscience science and remote sensing symposium, IGARSS’2009, IEEE International, South Africa.

[13] M. Le, V. Chandrasekar and S.Lim , Microphysical retrieval from dual-frequency GPM observations, 34th Conf on Radar Meteorology. Amer. Meteor. Soc., Williamsburg, VA, 2009.

[14] V. Chandrasekar, Direk, Khajonrat, and Minda Le, Tropical Cyclone Nargis over Myanmar: Vertical structure and Microphysics based on Space-based Radar observations, Proc IEEE IGARSS’2008, Boston.

[15] Eugenio Gorgucci, Luca Baldini, V. Chandrasekar and Minda Le, Reflectivity and differential reflectivity rainfall algorithm performance at X-band, Proc IEEE IGARSS’2008, Boston.


Program of Study:
ECE795
ECE799
ECE512
EE742
EE549
EE672
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